By cutting prices by close to 50 percent to its entry level Power Systems servers, IBM is trying to attract small and medium businesses to its big data and analytics platforms.
The company announced February 5 that it has created servers that cost $5,947. These servers feature a new series of IBM Power 7+ processors and more memory that can easily be tuned for analytical workloads.
Steve Silbey, IBM’s director of worldwide product management for Power Systems, said the lower prices offer small and medium size businesses an entry into IBM’s big data analytics products, and provide a competitive price point for smaller use cases in enterprise clients.
The price brings costs in line with Intel-based commodity hardware from Dell and HP that can be used to run open source data platforms like Hadoop. The new entry level Power Systems server costs about half as much as the previous IBM model, and features up to 40 percent better performance depending on the configuration, Sibley said.
“Obviously, competition always plays a little bit of a factor,” Sibley said. “But we really are trying to extend our reach to a new set of clients, and to a new set of workloads.”
IBM doesn’t necessarily see open source projects like Hadoop as competitors, Sibley said; the company has several partnerships with commercial open source companies. But the open source market for data management and analytics is growing, and there is an undeniable cost consideration for free software that can run on commodity hardware.
Barry Devlin, an industry consultant at 9Sight Consulting who focuses on data management and analytics, is a former IBMer. He helped develop IBM’s data warehouse architecture in the 1980s, and left the company in 2008.
Devlin said IBM has had trouble penetrating the small and medium business market for years. He said this drop in price for an analytics-capable server comes during a cultural shift for small business, a realization that data analytics are useful and within reach—and now IBM can offer a competitive choice to businesses entering the analytics world, backing their server hardware with IBM’s software and support.
“There are certain benefits to the open source environment, and of course one of them is price,” Devlin said. “You’ve got to balance it if you’re in the marketplace as a small or medium enterprise where it is you’re willing to take your risks, and where you’re willing to put your money.”
Devlin pointed out an entry into analytics comes with the necessity for data governance and data quality, however; analytics aren’t any good if your data isn’t clean and consistent. IBM can offer an integrated; all-in-one product that helps smaller IT shops by simplifying the technology.
“The message from IBM is: ‘We’ve got the services, we’ve got the software, we’ve got the hardware, we’ve put it into an integrated package and we’re there to stand behind you,” he said. “That’s the sort of thing that will appeal to a certain set of small and medium businesses where they do see that analytics is part of their core value.”
Sibley said that message is especially important because to companies just entering the analytics market because they often don’t have people to stand up and manage a full system on their own.
“We like to add our experience to the value we have in the technology, to help clients to take advantage of that more quickly and more easily, so they don’t always have to be open source, data or networking experts,” Sibley said. “They can get some of that expertise from us, either packaged into a system or through some services. Because of their IT resources, they need the answers quicker because they don’t have the time to wait, or the dedicated personnel.”
Sibley said enterprise level clients, where IBM has been a mainstay, have also started to deploy certain workloads on commodity-based servers simply because of the price, so that’s another segment IBM is trying to reach.
IBM announced other hardware products on Feb. 5, including a PureData System for Analytics aimed at larger enterprise customers that features 50 percent greater data capacity and the ability to crunch data three times faster than the previous generation. IBM also announced new software additions to its big data platforms, and private cloud options.
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